Key Takeaways
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Muse Glimmer is a new AI model from Meta.
It has 30 billion parameters.
It focuses on local AI agents.
It can understand text and images.
It supports 100+ languages.
It can help with coding and tool use.
It uses quantization for smaller size.
It uses speculative decoding for faster generation.
It is available as an open-weight model under the Apache 2.0 licence.
It was introduced on August 10, 2026.
Meta has introduced a new Artificial Intelligence (AI) model called Muse Glimmer. It was introduced on August 10, 2026, by Meta Superintelligence Labs.
Muse Glimmer is a 30-billion-parameter AI model. It is designed to run directly on computers. It can work without always depending on cloud servers or an internet connection.
Key Facts About Muse Glimmer
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Feature
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Details
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Model
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Muse Glimmer
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Developed by
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Meta Superintelligence Labs
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Parameters
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30 billion
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Released
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August 10, 2026
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Licence
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Apache 2.0
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Main focus
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Local AI agents
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Languages
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100+
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Input
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Text and images
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Model size after quantization
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Under 20 GB
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Main uses
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Coding, reasoning and tool use
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Source: meta
What is Muse Glimmer?
Muse Glimmer is an open-weight AI model made mainly for local AI agents.
An AI agent can perform several steps to complete a task. Muse Glimmer can help with coding, tool use, reasoning and understanding images.
Meta has released its model weights under the Apache 2.0 licence.
What is the Objective of Muse Glimmer?
The main objective is to make AI agents work efficiently on local devices.
Main objectives:
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Run AI directly on computers
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Reduce dependence on cloud servers
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Support AI agents
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Help with coding tasks
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Use different digital tools
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Work with text and images
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Support offline AI use
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Give developers an open AI model
What are the Different task can Muse Glimmer do?
Muse Glimmer has been designed for different AI tasks.
Multi-step tasks
It can plan and work through several steps to complete a task.
Tool use
It can use digital tools through function calls.
Coding
It can write, understand and debug code.
Error recovery
If a tool fails, it can identify the problem and try again.
Image understanding
It can understand screenshots, charts and documents.
Multilingual support
It has been trained using data from more than 100 languages.
Muse Glimmer vs Other AI Models
Meta compared Muse Glimmer with models such as Gemma 4 31B and Qwen3.6 27B.
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Feature
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Muse Glimmer
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Gemma 4 31B
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Qwen3.6 27B
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Parameters
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30 billion
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31 billion
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27 billion
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Local use
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Major focus
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Supported
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Supported
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Coding
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Yes
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Yes
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Yes
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AI agents
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Strong focus
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Yes
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Yes
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Multimodal use
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Text + images
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Multimodal
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Multimodal
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How Does Muse Glimmer Run Locally?
A 30-billion-parameter model can need more than 55 GB of memory at full precision.
Meta uses quantization to reduce its size.
With around 4-bit precision, Muse Glimmer can be reduced to under 20 GB.
This makes it more suitable for computers with around 24 GB or 32 GB of memory.
What is Speculative Decoding?
Muse Glimmer also uses speculative decoding to improve speed.
A smaller model first suggests several tokens. The main model then checks them.
This can make responses faster while keeping the output quality.
Why is Muse Glimmer Important?
Muse Glimmer focuses on local AI.
This can provide several benefits:
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AI can run directly on a computer.
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Internet may not always be needed.
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Developers get more control.
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Local AI agents can be built.
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Users can experiment with an open-weight model.
Where is Muse Glimmer Available?
Meta has released the model weights through Hugging Face.
It also provides developer documentation.
The model is being integrated with tools such as:
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llama.cpp
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MLX
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ExecuTorch
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Ollama
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LM Studio
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Unsloth
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vLLM
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SGLang
Muse Glimmer is designed to bring powerful AI agents directly to personal computers. Its focus on local use, coding, tool calling and multi-step tasks makes it an important development in agentic AI.